Candace Owens’ claim this morning that newly released CDC data proves that the coronavirus pandemic is a “hoax” is not supported by the data. In the post, she writes, “94% of American coronavirus deaths had underlying conditions like heart disease. Less than 10,000 Americans died from Coronavirus alone.”

If my own Facebook feed is any indication, lots of people also believe that data that were “quietly” (read: sneakily, dishonestly) released by the CDC this week have exposed the Covid pandemic as fake news.

A blogpost on Gateway Pundit making this claim has been liked and shared 140,000 times on Facebook. The headline: “SHOCK REPORT: This Week CDC Quietly Updated COVID-19 Numbers – Only 9,210 Americans Died From COVID-19 Alone – Rest Had Different Other Serious Illnesses”

Gateway Pundit writes, “So let’s get this straight – based on the recommendation of doctors Fauci and Birx the US shut down the entire economy based on 9,000 American deaths due entirely to the China coronavirus?”


To debunk this claim, I’m not even going to look at the “new” CDC data that are being cited by Owens and others. I think the data are being seriously misinterpreted by some people. But there are other people explaining why, and better than I can (here’s a great video that says everything I would want to say on the topic).

Instead, I’m going to look at a completely different CDC data set. I’ve been watching this data set for months now. And I don’t think it’s gotten nearly the attention it deserves.

The first column on the first chart on this page here (reproduced below) shows the number of deaths in the U.S. in which Covid is believed to have played a role. However, ignore that column for now. That number is exactly what’s in dispute right now, and I don’t want it to distract from my point.

Instead, look at the second column, the one that says “deaths from all causes.” Even more importantly, look at the next column, which shows the “percent of expected deaths.” (CONTINUED BELOW IMAGE)

In order to arrive at the “percent of expected deaths,” the CDC compiles the number of deaths (from all causes) from the previous three years, and then takes the average for each week. Then, they compare the number of deaths that have happened this year to the average of the previous three years, for the same time period.

If the percentage is below 100, that means fewer people died this year than the average from the previous three years. If the percentage is above 100, that means that more people died this year than the historical average.

Now, a glance at the chart is enough to show that something big started to happen in late March in the United States.

Up until late March, deaths for this year closely tracked the historical average. Suddenly, however, in the final week of March, they climbed to 12% higher than the historical average. Then, deaths continued to climb sharply, before peaking at forty-two percent higher than the historical average, in the second week of April.

To put this 42% increase into perspective, this means that some 23,000+ more people died in a single week – the second week of April – than we would have expected to die that week, based upon historical averages.

And though the number of deaths has dropped since that peak in early April, in no week since then has the percentage of expected deaths dropped below 110% (NOTE: There is a time lag on this chart, so the data is only complete up until about seven or eight weeks ago.)

In fact, if you add up the “excess deaths” for every week since this pandemic began, you find that there have been more excess deaths in the U.S. this year than the number of deaths attributed (whether wholly, or in part) to Covid.

Here’s another striking visualization of this data, showing the percentage of expected deaths compared to actual deaths over the past three years.

Again, a glance at the chart is enough to reveal a consistent trend of above-average deaths, starting in March of this year.

Now, the question is, what started happening in late March that might have led to this significant increase in deaths?

Well, certainly the arrival and spread of Covid in the United States is the leading candidate.

Now, I fully admit that this “excess death” data does not amount to iron-clad proof that Covid has killed this many people. After all, correlation does not equal causation.

This increase in deaths in the U.S. could, in theory, have been caused by something else: by, for example, a horrible flu season, or collateral damage caused by the lockdowns, rather than the virus that the lockdowns were designed to combat.

Could be…could be. But, is it likely?

Is it likely – as the Gateway Pundit post implies – that the CDC, governors of numerous states, and tens of thousands of doctors, nurses, and other healthcare experts, all somehow missed the fact that this virus was only actually killing a tiny fraction (6%) of the number of people that official data claimed? And is it likely that hundreds of countries around the world shut down travel and their economies, to stop a virus that was actually only killing 6% of the number of people we thought it was?

And, on top of that, is it likely that tens of thousands of additional people started dying in the U.S. at precisely the time that Covid infection rates started climbing, but from some other cause than Covid?

I don’t think so.

So, in answer to Gateway Pundit’s question, we did not “shut down the entire economy based on 9,000 American deaths due entirely to the China coronavirus”. We shut it down because a lot of people were dying. True, lots of people were dying in part because they had comorbidities – but the excess death stats sure suggest that a lot of them wouldn’t have died, were it not for the fact that they also had Covid. (Also, it seems many people are misunderstanding the comorbidity data, since some of the comorbidities listed on the death certificates are not necessarily things the deceased had before getting Covid, but would in fact have been caused by Covid.)

Let me conclude with a final caveat: None of this is intended to address the question of whether or not the lockdowns, mask mandates, or other measures taken to respond to this virus were proportionate or not. Nor is any of this intended to weigh in on precisely how bad this pandemic is, compared to what the models and experts predicted, or to how the media has portrayed it, or to prior pandemics. Even if we acknowledge that Covid has contributed to or caused the deaths of a lot more than the 9,000 people whose death certificates mention Covid alone, there is a lot of room for debate about how we should have handled all this.

There are also nuances within the excess death statistics that need to be discussed: e.g. how many of those who died this year were elderly people with significant comorbidities, who would have died within the year even without Covid? For such people as these, Covid – yes – was likely a contributing factor to their death, but if they make up a significant percentage of Covid-related deaths, then that certainly affects the debate about the efficacy or proportionality of the lockdowns, etc.

But these debates needs to start from an accurate understanding of the data, not the application of preconceived narratives to the data.

P.S. We are swimming in data at this point, and it may be that there are other data that call into question this analysis. By all means, comment below if my analysis is inaccurate or incomplete in any way.

Published by John Jalsevac

I am a PhD student in philosophy.

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